Gradient Boosting algorithm

This paper presents a comprehensive investigation into applying machine learning techniques for predicting the MS of basalt fiber asphalt concrete. The study leverages the Gradient Boosting algorithm to establish predictive models.

19p visharma 20-10-2023 6 4   Download

Within its range, the Caspian green lizard, Lacerta strigata, occurs in the Elburz Mountains (northern Iran) at elevations from below sea level to approximately 2700 m a.s.l. To determine the environmental factors affecting the distribution of this lizard, we used an ensemble approach to model the distribution of the Caspian green lizard (Lacerta strigata) in Iran using four algorithms (generalized boosted model, maximum entropy, generalized linear model, random forest).

8p dolomite36 30-12-2021 8 0   Download

In clinical research prediction models are used to accurately predict the outcome of the patients based on some of their characteristics. For high-dimensional prediction models (the number of variables greatly exceeds the number of samples) the choice of an appropriate classifier is crucial as it was observed that no single classification algorithm performs optimally for all types of data.

17p vikentucky2711 24-11-2020 12 1   Download

This paper discusses predicting attendance at Major League Soccer events using data from the 2014 and 2015 seasons. Panel data is obtained for each team, season, and weather category. A traditional least squared dummy variable linear regression technique is used along with three machine learning algorithms – random forest, M5 prime, and extreme gradient boosting. Extreme gradient boosting provides superior results with respect to out-of-sample root mean square error statistics.

8p guestgreat 16-05-2019 32 0   Download